Evaluating urinary metabolic profiles with wildland-urban-interface (wui) fire exposure among male firefighters: a comparison with municipal structure fires (msf).

backgroundFirefighters have frequent exposure to carcinogens and an increased risk of cancer. Wildland-urban interface (WUI) fires, which involve both structures and undeveloped wildland fuels, pose unique challenges to the health of firefighters. However, the extent of health risks associated with these fires remains underexplored.

objectivesThis study aims to identify altered urine metabolites and metabolic processes among male firefighters that were associated with WUI fires as compared with municipal structure fires (MSF).

methodsUntargeted metabolomic profiling was applied to pre-exposure (baseline) and postfire urine samples collected from firefighters responding to WUI and MSF fires. Differential analysis was conducted by fitting linear mixed effects regression models on preprocessed ion intensity and exposure status while adjusting for demographic covariates. Differential metabolites by post-exposure status were identified using a false discovery rate (FDR) threshold of < 0.05. Pathway analysis was performed to identify pathways that were significantly perturbed at a Bonferroni adjusted p-value < 0.05 level. We conducted differential and pathway analyses in both the WUI and MSF cohorts and compared the two fire types in terms of the number of differentially expressed metabolites and patterns of metabolic pathway enrichment.

resultsEighty-five firefighters contributed paired baseline and post-fire samples from WUI events, and 98 firefighters contributed paired baseline and post-fire samples from MSF events. We performed metabolic profiling on baseline and postfire urine samples from WUI and MSF using four modes: HILIC(-), HILIC(+), C18(-), and C18(+) and identified metabolites against an in-house library. We identified 244, 297, 320, and 266 level-1 metabolites from the four respective modes. In the statistical analysis, the main model identified a total of 176 differential metabolites from WUI fires. For MSF, the model identified a total of 652 differential metabolites from the four respective modes. Most metabolites with significant changes after a WUI fire also changed significantly after an MSF event. Two metabolic pathways were significantly enriched after WUI fires, while 7 pathways were significantly enriched after MSF exposure and 2 pathways overlapped between the two types of fires.

conclusionFire exposure induces numerous metabolic perturbations in firefighters responding to WUI fires, potentially contributing to their elevated cancer risk. Although individual metabolites changed in a similar fashion across both WUI and MSF, MSF were associated with an increased number of metabolite changes and some of the enriched pathways differed between exposures to WUI fires vs. MSF. These findings suggest that WUI and MSF exposures may share common biological responses while also posing unique health risks to firefighters.